BRIEF RESEARCH REPORT article
Front. Nephrol.
Sec. Clinical Research in Nephrology
Volume 5 - 2025 | doi: 10.3389/fneph.2025.1607017
Article Type: Brief research report Artificial Intelligence in Nephrology Education: A Multicenter Survey of Fellowship Trainees at Mayo Clinic
Provisionally accepted- 1Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Michigan, United States
- 2Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Jacksonville, FL, United States
- 3Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Phoenix, AZ, United States
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Background: Artificial intelligence (AI) is increasingly recognized for its potential to enhance nephrology training and practice. However, its integration into fellowship training remains inadequately explored. This study aimed to assess current AI utilization, perceptions, and educational needs among nephrology fellows at Mayo Clinic.Methods: A structured online survey was administered to 23 fellows—including those in transplant and onco-nephrology—across Mayo Clinic sites in Minnesota, Arizona, and Florida. The survey addressed domains such as AI usage, perceived relevance in clinical practice, interest in formal AI training, self-assessed comfort with AI integration, and barriers to adoption.Results: A total of 21 fellows (91% response rate) completed the survey. Seventy-six percent rated AI as moderately to highly relevant, and an equal percentage expressed moderate to very high interest in AI training. Despite this, 76% had rarely or never used AI clinically or in research, and none reported formal training. Interactive workshops were the preferred training format (52%), while limited knowledge was the most cited barrier. Optimism was highest for predictive modeling (86%) and diagnostic imaging (81%), whereas confidence in AI for clinical decision-making remained cautious.Conclusion: Nephrology fellows demonstrate strong interest in AI but lack exposure and training. This enthusiasm, coupled with a cautious approach to clinical application, underscores the urgent need for educational initiatives to bridge the knowledge gap and build confidence in using AI in nephrology fellowship.
Keywords: artificial intelligence, Nephrology fellowship, Educational needs, clinical decision-making, fellowships, Health Knowledge
Received: 06 Apr 2025; Accepted: 03 Jun 2025.
Copyright: © 2025 Sheikh, Thongprayoon, Craici, Miao, Qureshi, Mao, Hommos, Prendergast, Nair, Kashani and Cheungpasitporn. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Wisit Cheungpasitporn, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, 55905, Michigan, United States
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.